A Semantic-Enabled Common Data Environment for Real-Time Digital Twin Applications in Small-Scale Construction Projects - Minh, Nhat Nguyen; Trung, Tuan Nguyen (Civil Engineering Journal, 2025)
The integration of Building Information Modeling (BIM) and Digital Twin (DT) systems has reshaped construction project delivery, but their application remains concentrated in large, resource-intensive developments. Small-scale projects, which dominate the built environment in many regions, often lack access to advanced digital platforms due to financial constraints, insufficient infrastructure, and limited technical capacity. Existing Common Data Environment (CDE) frameworks are typically monolithic and costly, making them unsuitable for the flexible and affordable deployment needed in these contexts. A persistent barrier is semantic fragmentation: without interoperable data exchange across BIM, Internet of Things (IoT) devices, and Geographic Information Systems (GIS), project information remains siloed and underutilized. This study introduces a modular, semantic-enabled CDE architecture designed specifically for small-scale projects. The framework incorporates lightweight ontologies, microservices, and knowledge graphs to deliver scalable and semantically coherent integration of BIM–IoT–GIS datasets. To validate its applicability, the research applies the model to a three-storey educational building, demonstrating how real-time DT functionality can be achieved with minimal infrastructure demands. The case study highlights improvements in data exchange, operational monitoring, and sustainability analysis, showing how the architecture supports predictive maintenance and decision-making. By synthesizing insights from literature and practical demonstration, the paper proposes a blueprint for democratizing DT adoption, enabling affordable, adaptable, and interoperable solutions for small-scale construction projects.